allowances for a psychological trait, which has been confirmed by a large body of
experimental study: people overestimate low probabilities and underestimate high
probabilities.
Another anomaly well known to economists is ambiguity aversion. This characteristic was suggested by Keynes and latter demonstrated by Ellsberg [8] in the
form of a paradox. In his treatise on probabilities Keynes [9] posited that greater
weight is given to a probability that is certain to one that is imprecise. Ellsberg has
shown that just as there is a premium for taking risks, some compensation must be
awarded to individuals for them to be indifferent to gain (or lose) with a one-in-two
probability or an unknown probability with an expected value of one-in-two.
Recent developments in economic theory offer several solutions to tackle this
problem, in particular by specifying new types of utility functions, yet again [10].
What is important to keep in mind here is that individuals usually prefer the
exposure to a hazard associated with a clearly defined probability—because experts
are in agreement—rather than the exposure to a hazard characterized by uncertain
or fuzzy probabilities—because experts may disagree. Putting it another way, in the
second instance people side with the expert predicting the worst-case scenario.
More recently, Kahneman’s work followed on that of Bernouilli, Allais and
Ellsberg. He and his fellow author, Tversky, introduced loss-aversion: individual
are more affected by loss than gain [11]. Kahneman also diverged from his predecessors in adopting a more positive approach. Observing the distortion of
probabilities is a way to understand how our brain works rather than to build a
theory where the decision-maker optimizes or maximizes the outcome. Kahneman’s
line of research is comparable to subjecting participants to optical illusions to gain a
better understanding how our brain functions. For example, a 0.0001 probability of
loss will be perceived as lower than a 1/10,000 probability. Our brain seems to be
misled by the presentation of figures, much as our eyes are confused by an optical
effect which distorts an object’s size or perspective. This bias seems to suggest than
our brain takes a short cut and disregards the denominator, focusing only on the
numerator.
2.4 The Effects of Perception Biases on Nuclear Accidents
The overall biases in our perception of probabilities, briefly discussed above,
amplify the risk of a nuclear accident in our minds. A nuclear accident is a rare
event, so its probability is overestimated. The risk of a nuclear accident is
ambiguous. As expert appraisals diverge, people are therefore inclined to opt for the
worst-case scenario. The highest probability of accident prevails. Along with plane
crashes or terrorist attacks targeting markets, hotels or buses, a nuclear accident is a
dreadful event. Rather than acknowledging the probability of the accident, attention
focuses exclusively on the accident itself, disregarding the denominator. Moreover,
several other common routines or heuristics which have been identified by
The Economic Assessment of the Cost of Nuclear Accidents
85
experimental study: people overestimate low probabilities and underestimate high
probabilities.
Another anomaly well known to economists is ambiguity aversion. This characteristic was suggested by Keynes and latter demonstrated by Ellsberg [8] in the
form of a paradox. In his treatise on probabilities Keynes [9] posited that greater
weight is given to a probability that is certain to one that is imprecise. Ellsberg has
shown that just as there is a premium for taking risks, some compensation must be
awarded to individuals for them to be indifferent to gain (or lose) with a one-in-two
probability or an unknown probability with an expected value of one-in-two.
Recent developments in economic theory offer several solutions to tackle this
problem, in particular by specifying new types of utility functions, yet again [10].
What is important to keep in mind here is that individuals usually prefer the
exposure to a hazard associated with a clearly defined probability—because experts
are in agreement—rather than the exposure to a hazard characterized by uncertain
or fuzzy probabilities—because experts may disagree. Putting it another way, in the
second instance people side with the expert predicting the worst-case scenario.
More recently, Kahneman’s work followed on that of Bernouilli, Allais and
Ellsberg. He and his fellow author, Tversky, introduced loss-aversion: individual
are more affected by loss than gain [11]. Kahneman also diverged from his predecessors in adopting a more positive approach. Observing the distortion of
probabilities is a way to understand how our brain works rather than to build a
theory where the decision-maker optimizes or maximizes the outcome. Kahneman’s
line of research is comparable to subjecting participants to optical illusions to gain a
better understanding how our brain functions. For example, a 0.0001 probability of
loss will be perceived as lower than a 1/10,000 probability. Our brain seems to be
misled by the presentation of figures, much as our eyes are confused by an optical
effect which distorts an object’s size or perspective. This bias seems to suggest than
our brain takes a short cut and disregards the denominator, focusing only on the
numerator.
2.4 The Effects of Perception Biases on Nuclear Accidents
The overall biases in our perception of probabilities, briefly discussed above,
amplify the risk of a nuclear accident in our minds. A nuclear accident is a rare
event, so its probability is overestimated. The risk of a nuclear accident is
ambiguous. As expert appraisals diverge, people are therefore inclined to opt for the
worst-case scenario. The highest probability of accident prevails. Along with plane
crashes or terrorist attacks targeting markets, hotels or buses, a nuclear accident is a
dreadful event. Rather than acknowledging the probability of the accident, attention
focuses exclusively on the accident itself, disregarding the denominator. Moreover,
several other common routines or heuristics which have been identified by
The Economic Assessment of the Cost of Nuclear Accidents
85